Skill UI

This skill details the deployment of various canary tokens (DNS, HTTP, AWS API Keys) across enterprise network infrastructure. It establishes digital tripwires that detect behavioral anomalies, such as unauthorized access, credential leakage, or lateral movement. Tokens are configured with webhook alerts (Slack, SIEM) for real-time, low-false-positive notification, significantly enhancing traditional IDS/IPS capabilities.

This skill uses advanced AI and LLM capabilities to correlate fragmented Open Source Intelligence (OSINT) data. It ingests findings from diverse sources—including username enumeration, email lookups, social media, domain records, and breach databases—to generate unified, intelligence-grade profiles. It provides link analysis and confidence scoring, transforming raw data into actionable threat intelligence for target profiling.

Transformers.js allows developers to run state-of-the-art machine learning models directly within JavaScript/TypeScript environments (browser, Node.js). It supports a comprehensive range of tasks including NLP (text generation, summarization, translation), Computer Vision (image classification, object detection), and Audio processing. This capability enables building fully client-side, multimodal AI applications without requiring a dedicated Python backend or server infrastructure.

This skill provides a comprehensive, read-only audit of a development workspace, including active repositories, installed plugins, connected services, and environment configurations. It analyzes existing capabilities against best practices to identify functional gaps and recommends the most valuable ECC-native skills, hooks, and workflows needed to enhance the development experience. Ideal for setup planning and architectural reviews.

AgentPhone is an API-first platform designed for developers building AI agents with advanced telephony capabilities. It allows agents to manage phone numbers, make/receive voice calls, and handle SMS messages. Developers can utilize hosted mode for simple AI interactions or webhook mode for custom, complex logic, making it ideal for building sophisticated customer support bots or virtual assistants.

A behavioral psychologist skill designed to ethically engineer genuine scarcity and urgency mechanics. This tool helps structure compelling messaging that motivates immediate action by leveraging real limitations (inventory, time, capacity) rather than misleading claims. It ensures persuasive communication remains trustworthy and preserves audience autonomy.

This skill file acts as a Japanese translation placeholder for the 'product-capability' module. It indicates that the localized content is currently under development and not functional. Users should refer to the original English skill file for the core functionality and detailed implementation.

Discover, download, and manage reusable AI agent skills from the AionUI Skills registry, making it easy to augment autonomous assistants with community-built capabilities whenever a task benefits from specialized functionality.

A comprehensive guide and function for discovering, searching, and securely installing modular agent skills from an open ecosystem. It helps users identify specialized capabilities needed for domains like web development, testing, or DevOps, utilizing the `npx skills` CLI. The skill emphasizes best practices, including checking skill reputation and requiring explicit user confirmation before running code.

A comprehensive guide for integrating and utilizing Firebase Data Connect within Flutter applications. Learn how to set up schemas, write typed GraphQL queries and mutations, handle real-time data streams, implement robust offline capabilities, and apply best practices for security and performance.

A comprehensive guide for advanced Go developers, detailing the internals, optimal usage, and performance pitfalls of core data structures like slices, maps, and arrays. It covers capacity growth mechanics, preallocation strategies using `make` and `slices` package functions, and best practices for choosing between various standard library containers (e.g., `strings.Builder` vs `bytes.Buffer`). Essential for writing highly efficient, memory-safe Go code.

Improves Go error handling by treating errors as structured data. This utility adds critical context—such as domain, user IDs, stack traces, and machine-readable error codes—to standard Go errors. This capability is vital for enhancing observability, enabling APM tools (like Sentry or Datadog) and on-call engineers to diagnose complex issues quickly without relying on manual log correlation.